The derived numbers, characteristics and outcomes of patients with the luminal A like and luminal B like subtypes under our proposed definitions would be comparable to those observed in studies in which researchers have defined intrinsic molecular subtypes by utilizing gene expression profiling.
Wu et al. 14 similarly proposed a network-analysis-based model that utilized gene expression profiles, following individual treatments, to predict gene expression changes induced by drug combinations, which were then used to estimate the effectiveness of the combinations.
One study utilizes gene expression profiling for predicting therapeutic response to docetaxel [ 1].
This is the first study to utilize gene expression profiling to examine global gene expression in response to acute β2-AR agonist treatment of skeletal muscle.
This proportion is much the same as that observed by study researchers who have defined intrinsic molecular subtypes by utilizing gene expression profiling [ 7, 8].
In brief, the algorithm utilizes gene expression profiles of cell populations harvested from mouse tissues (mostly leukocytes; e.g., T-cells, DCs, macrophages), and for each population, a set of "signature transcripts" is identified, which consists of transcripts highly expressed in that population relative to normal mouse skin.
We have developed a relational database to store, manage and maximally utilize gene expression profile data collected from multiple investigators in Cincinnati Children's Hospital Medical Center, Division of Pulmonary Biology.
We developed models for utilizing gene expression profile to predict the class of future samples based on the Diagonal Linear Discriminant Analysis and Nearest Neighbour Classification [ 11].
In conclusion, EXPath, freely available at http://expath.itps.ncku.edu.tw, is a database resource that collects and utilizes gene expression profiles derived from microarray platforms under various conditions to infer metabolic pathways for plants.
